Improved Uncertainty Analysis for Tidal Energy Project Development

Abstract

High investment risk is a key barrier to the commercialisation of the nascent tidal energy sector. An increase in investor confidence can unlock funding for early arrays, the lessons from which can provide further de-risking, leading to further investment. Investment decisions are based not only on the most likely expectations of a project's performance, but also on the likelihood of performance deviations. The likelihood of deviations is quantifi ed using uncertainty analysis. This thesis recommends improvements to commonly used uncertainty analysis methods for quantifying the uncertainty in a tidal energy project's key investment metrics; energy yield, levelised cost of energy (LCOE) and internal rate of return (IRR). The potential for the commonly used methods to lead to misinformed investment decisions being made is demonstrated. Simpler solutions, which still provide an improved accuracy in uncertainty estimates, are also suggested for cases where the use of the most accurate method is not practical. The overall result is an increased confi dence in the uncertainty estimates for key investment metrics used to appraise the financial viability of tidal energy projects.